1 =========================================
2 A guide to Dockerfiles for building LLVM
3 =========================================
7 You can find a number of sources to build docker images with LLVM components in
8 ``llvm/utils/docker``. They can be used by anyone who wants to build the docker
9 images for their own use, or as a starting point for someone who wants to write
10 their own Dockerfiles.
12 We currently provide Dockerfiles with ``debian8`` and ``nvidia-cuda`` base images.
13 We also provide an ``example`` image, which contains placeholders that one would need
14 to fill out in order to produce Dockerfiles for a new docker image.
18 Docker images provide a way to produce binary distributions of
19 software inside a controlled environment. Having Dockerfiles to builds docker images
20 inside LLVM repo makes them much more discoverable than putting them into any other
25 If you've never heard about Docker before, you might find this section helpful
26 to get a very basic explanation of it.
27 `Docker <https://www.docker.com/>`_ is a popular solution for running programs in
28 an isolated and reproducible environment, especially to maintain releases for
29 software deployed to large distributed fleets.
30 It uses linux kernel namespaces and cgroups to provide a lightweight isolation
31 inside currently running linux kernel.
32 A single active instance of dockerized environment is called a *docker
34 A snapshot of a docker container filesystem is called a *docker image*.
35 One can start a container from a prebuilt docker image.
37 Docker images are built from a so-called *Dockerfile*, a source file written in
38 a specialized language that defines instructions to be used when build
39 the docker image (see `official
40 documentation <https://docs.docker.com/engine/reference/builder/>`_ for more
41 details). A minimal Dockerfile typically contains a base image and a number
42 of RUN commands that have to be executed to build the image. When building a new
43 image, docker will first download your base image, mount its filesystem as
44 read-only and then add a writable overlay on top of it to keep track of all
45 filesystem modifications, performed while building your image. When the build
46 process is finished, a diff between your image's final filesystem state and the
47 base image's filesystem is stored in the resulting image.
51 The ``llvm/utils/docker`` folder contains Dockerfiles and simple bash scripts to
52 serve as a basis for anyone who wants to create their own Docker image with
53 LLVM components, compiled from sources. The sources are checked out from the
54 upstream svn repository when building the image.
56 The resulting image contains only the requested LLVM components and a few extra
57 packages to make the image minimally useful for C++ development, e.g. libstdc++
60 The interface to run the build is ``build_docker_image.sh`` script. It accepts a
61 list of LLVM repositories to checkout and arguments for CMake invocation.
63 If you want to write your own docker image, start with an ``example/`` subfolder.
64 It provides an incomplete Dockerfile with (very few) FIXMEs explaining the steps
65 you need to take in order to make your Dockerfiles functional.
69 The ``llvm/utils/build_docker_image.sh`` script provides a rather high degree of
70 control on how to run the build. It allows you to specify the projects to
71 checkout from svn and provide a list of CMake arguments to use during when
72 building LLVM inside docker container.
74 Here's a very simple example of getting a docker image with clang binary,
75 compiled by the system compiler in the debian8 image:
79 ./llvm/utils/docker/build_docker_image.sh \
81 --docker-repository clang-debian8 --docker-tag "staging" \
82 -p clang -i install-clang -i install-clang-resource-headers \
84 -DCMAKE_BUILD_TYPE=Release
86 Note that a build like that doesn't use a 2-stage build process that
87 you probably want for clang. Running a 2-stage build is a little more intricate,
88 this command will do that:
92 # Run a 2-stage build.
93 # LLVM_TARGETS_TO_BUILD=Native is to reduce stage1 compile time.
94 # Options, starting with BOOTSTRAP_* are passed to stage2 cmake invocation.
95 ./build_docker_image.sh \
97 --docker-repository clang-debian8 --docker-tag "staging" \
98 -p clang -i stage2-install-clang -i stage2-install-clang-resource-headers \
100 -DLLVM_TARGETS_TO_BUILD=Native -DCMAKE_BUILD_TYPE=Release \
101 -DBOOTSTRAP_CMAKE_BUILD_TYPE=Release \
102 -DCLANG_ENABLE_BOOTSTRAP=ON -DCLANG_BOOTSTRAP_TARGETS="install-clang;install-clang-resource-headers"
104 This will produce a new image ``clang-debian8:staging`` from the latest
106 After the image is built you can run bash inside a container based on your image
111 docker run -ti clang-debian8:staging bash
113 Now you can run bash commands as you normally would:
117 root@80f351b51825:/# clang -v
118 clang version 5.0.0 (trunk 305064)
119 Target: x86_64-unknown-linux-gnu
122 Found candidate GCC installation: /usr/lib/gcc/x86_64-linux-gnu/4.8
123 Found candidate GCC installation: /usr/lib/gcc/x86_64-linux-gnu/4.8.4
124 Found candidate GCC installation: /usr/lib/gcc/x86_64-linux-gnu/4.9
125 Found candidate GCC installation: /usr/lib/gcc/x86_64-linux-gnu/4.9.2
126 Selected GCC installation: /usr/lib/gcc/x86_64-linux-gnu/4.9
127 Candidate multilib: .;@m64
128 Selected multilib: .;@m64
131 Which image should I choose?
132 ============================
133 We currently provide two images: debian8-based and nvidia-cuda-based. They
134 differ in the base image that they use, i.e. they have a different set of
135 preinstalled binaries. Debian8 is very minimal, nvidia-cuda is larger, but has
136 preinstalled CUDA libraries and allows to access a GPU, installed on your
139 If you need a minimal linux distribution with only clang and libstdc++ included,
140 you should try debian8-based image.
142 If you want to use CUDA libraries and have access to a GPU on your machine,
143 you should choose nvidia-cuda-based image and use `nvidia-docker
144 <https://github.com/NVIDIA/nvidia-docker>`_ to run your docker containers. Note
145 that you don't need nvidia-docker to build the images, but you need it in order
146 to have an access to GPU from a docker container that is running the built
149 If you have a different use-case, you could create your own image based on
152 Any docker image can be built and run using only the docker binary, i.e. you can
153 run debian8 build on Fedora or any other Linux distribution. You don't need to
154 install CMake, compilers or any other clang dependencies. It is all handled
155 during the build process inside Docker's isolated environment.
159 If you want a somewhat recent and somewhat stable build, use the
160 ``branches/google/stable`` branch, i.e. the following command will produce a
161 debian8-based image using the latest ``google/stable`` sources for you:
165 ./llvm/utils/docker/build_docker_image.sh \
166 -s debian8 --d clang-debian8 -t "staging" \
167 --branch branches/google/stable \
168 -p clang -i install-clang -i install-clang-resource-headers \
170 -DCMAKE_BUILD_TYPE=Release
173 Minimizing docker image size
174 ============================
175 Due to how Docker's filesystem works, all intermediate writes are persisted in
176 the resulting image, even if they are removed in the following commands.
177 To minimize the resulting image size we use `multi-stage Docker builds
178 <https://docs.docker.com/develop/develop-images/multistage-build/>`_.
179 Internally Docker builds two images. The first image does all the work: installs
180 build dependencies, checks out LLVM source code, compiles LLVM, etc.
181 The first image is only used during build and does not have a descriptive name,
182 i.e. it is only accessible via the hash value after the build is finished.
183 The second image is our resulting image. It contains only the built binaries
184 and not any build dependencies. It is also accessible via a descriptive name
185 (specified by -d and -t flags).